4.7 Article

Combining rainfall-induced shallow landslides and subsequent debris flows for hazard chain prediction

Journal

CATENA
Volume 213, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.catena.2022.106199

Keywords

Landslides; Debris flows; Coupled model; Hazard chain prediction

Funding

  1. Second Tibetan Plateau Scientific Expedition and Research Program (STEP) [2019QZKK0902]
  2. Natural Science Basic Research Program of Shaanxi [2021JC-40]
  3. International Science & Technology Cooperation Program of China [2018YFE0100100]

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In mountainous regions, rainfall-induced landslides, debris flows, and other natural hazards often form a chain of disasters. This study proposes a method that combines the TRIGRS model and the RAMMS model to achieve hourly hazard prediction. The TRIGRS model performs well in predicting the spatial distribution of shallow landslides, making it suitable for debris flow simulations. The coupled model accurately simulates debris flows and can dynamically predict disasters based on actual rainfall events. The results of this study are important for hazard prediction of rainfall-induced landslide-debris flow hazards in mountainous regions.
Landslides, debris flows, and other destructive natural hazards induced by heavy rainfall in mountainous regions are sometimes not independent but combined to form a disaster chain. Based on the integral link between the triggering of the landslide and the subsequent debris flow, we propose an approach that combines the Transient Rainfall Infiltration and Grid-Based Regional Slope Stability (TRIGRS) model and the Rapid Mass Movements Simulation (RAMMS) model to achieve hourly hazard prediction. The results indicate that the TRIGRS model performed well in predicting the spatial distribution of the shallow landslides, with a success rate of 81.86%. Thus, it is reasonable to use it as the initial input for debris flow simulations. The relationship between the landslide area and the accumulated rainfall obtained using the TRIGRS model is a power-law relationship, which provides a reference for regions that lack rainfall data to predict the material source of a debris flow. The coupled model was found to have a good accuracy of 76.77% in simulating the debris flow. This was close to the debris flow simulation based on the interpreted landslides, and it still produced reasonable results and a more practical value. Furthermore, the proposed coupled model can dynamically predict disasters by the hour based on actual rainfall events. Therefore, the results of this study help provide a more complete hazard prediction picture for rainfall-induced landslide-debris flow hazards in mountainous regions.

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